Mental health is an increasingly important problem in healthcare. Based on the data from the 2015 National Survey on Drug Use and Health (NSDUH), 1 in 5 adults experience a mental illness, and nearly 1 in 25 adults lives with a serious mental illness in the United States. Especially, the annual suicide rate in the U.S. has continued to climb over the past several decades and suicide is the 10th leading causes of death in the U.S. The economic impact of suicidal behavior has been estimated to exceed more than $51 billion annually in the U.S.
In recent years, there has been a rapid growth in the implementation of electronic health records (EHRs), leading to an unprecedented expansion in the availability of dense longitudinal datasets for clinical and translational research for psychiatric disorders. Meanwhile, the rapidly increasing, huge archive of consumer data in social media such as Twitter and Facebook also provides unprecedented opportunities to access a broad population with the mental health issues and suicidal behavior. The real-time information flow on social media makes it possible to monitor and provide early interventions to potential at-risk users, which is imperative for suicide prevention. Therefore, it is very important to extract risk factors, phenotyping information, and human behaviors automatically from EHRs and social media data. Moreover, the extracted information needs to be formally represented in an ontological semantic framework for further applications and reasoning. However, psychiatric information often shows unique characteristics, such as subjective descriptions of patient experience and idiosyncratic psychosocial backgrounds, leading to challenges of data sparseness and diversity. Novel natural language processing and ontology technologies are needed to address the challenges.
The goal of this special issue is to publish original research of innovative analytical methods, applications, and tools addressing problems in mental health, from experts in the field of natural language processing, knowledge representation, knowledge management, and health data analytics.
The manuscripts are also welcomed to the workshop of MentalHealth 2018 (pending), which will be published in the IEEE ICHI 2018 Proceedings (in IEEE Xplore Digital Library); Selected FULL/SHORT papers will be invited to publish an extended version in the supplement of Health Informatics Journal. Selected high-quality SHORT papers will also be invited to submit an extended version of the journal supplement for consideration.
Note: If a paper is selected for possible journal publication, the authors will be asked to shorten their workshop paper to be published in the ICHI 2018 Proceedings and then submit the journal version after the workshop. The authors can still choose to publish their full papers in the conference proceedings, in which case, however, the authors will NOT be eligible to publish in the journal supplement due to the journal's self-plagiarism concern.
Topics of interest include but not limited to:
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Deadline for paper submission |
April 9, 2018 |
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First-round notification |
May 9, 2018 |
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Second-round submission |
June 9, 2018 |
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Second-round notification |
July 9, 2018 |
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Notification of acceptance |
August 9, 2018 |
Please feel free to contact us at yaoyun.zhang@uth.tmc.edu, if you have any questions.